Sundararajan Sellamanickam
Sundararajan Sellamanickam
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A dual coordinate descent method for large-scale linear SVM
CJ Hsieh, KW Chang, CJ Lin, SS Keerthi, S Sundararajan
Proceedings of the 25th international conference on Machine learning, 408-415, 2008
Predictive approaches for choosing hyperparameters in Gaussian processes
S Sundararajan, SS Keerthi
Neural Computation 13 (5), 1103-1118, 2001
A sequential dual method for large scale multi-class linear SVMs
SS Keerthi, S Sundararajan, KW Chang, CJ Hsieh, CJ Lin
Proceeding of the 14th ACM SIGKDD international conference on Knowledge …, 2008
Learning hierarchical similarity metrics
N Verma, D Mahajan, S Sellamanickam, V Nair
2012 IEEE conference on computer vision and pattern recognition, 2280-2287, 2012
A joint learning framework for attribute models and object descriptions
D Mahajan, S Sellamanickam, V Nair
2011 International Conference on Computer Vision, 1227-1234, 2011
Lateral movement detection
RSS Kumar, NSK Vu, M DiPlacido, V Nair, A Das, M Swann, K Selvaraj, ...
US Patent 9,591,006, 2017
Hetegcn: heterogeneous graph convolutional networks for text classification
R Ragesh, S Sellamanickam, A Iyer, R Bairi, V Lingam
Proceedings of the 14th ACM international conference on web search and data …, 2021
Method for efficiently building compact models for large multi-class text classification
SK Selvaraj, D Pavlov, SJ Gaffney, NE Mayoraz, P Berkhin, V Krishnan, ...
US Patent App. 12/115,486, 2009
Learning a hierarchical monitoring system for detecting and diagnosing service issues
V Nair, A Raul, S Khanduja, V Bahirwani, Q Shao, S Sellamanickam, ...
Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015
CRF versus SVM-struct for sequence labeling
SS Keerthi, S Sundararajan
Yahoo Research Technical Report, 2007
Web information extraction using markov logic networks
S Satpal, S Bhadra, S Sellamanickam, R Rastogi, P Sen
Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011
A distributed block coordinate descent method for training l1 regularized linear classifiers
D Mahajan, SS Keerthi, S Sundararajan
Journal of Machine Learning Research 18 (91), 1-35, 2017
A pairwise ranking based approach to learning with positive and unlabeled examples
S Sellamanickam, P Garg, SK Selvaraj
Proceedings of the 20th ACM international conference on Information and …, 2011
A sequential dual method for structural SVMs
P Balamurugan, S Shevade, S Sundararajan, SS Keerthi
Proceedings of the 2011 SIAM International Conference on Data Mining, 223-234, 2011
Large scale entity-specific resource classification
SK Selvaraj, PL Bohannon, M Muralidharan, C Yu, A Machanavajjhala, ...
US Patent 9,317,613, 2016
Distributed newton methods for deep neural networks
CC Wang, KL Tan, CT Chen, YH Lin, SS Keerthi, D Mahajan, ...
Neural computation 30 (6), 1673-1724, 2018
Semi-supervised Gaussian process ordinal regression
PK Srijith, S Shevade, S Sundararajan
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2013
Towards resource-elastic machine learning
S Narayanamurthy, M Weimer, D Mahajan, T Condie, S Sellamanickam, ...
NIPS 2013 BigLearn Workshop 1 (2.1), 2-3, 2013
System and method for sparse gaussian process regression using predictive measures
S Sellamanickam, SK Selvaraj
US Patent App. 12/001,958, 2009
A parallel SGD method with strong convergence
D Mahajan, SS Keerthi, S Sundararajan, L Bottou
arXiv preprint arXiv:1311.0636, 2013
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